Prinicipal AI Engineer

Must Have Technical/Functional Skills Seeking a highly accomplished Principal AI Engineer to lead the design, architecture, and delivery of enterprise scale AI and Machine Learning solutions. This role requires deep technical expertise in AI/ML, strong architectural vision, hands-on leadership, and the ability to drive AI strategy across the organization. The ideal candidate has extensive experience with advanced ML systems, GenAI/LLM solutions, and end to end AI platform development. Key Responsibilities AI Strategy & Technical Leadership " Define and drive the organization's AI roadmap, architecture, and long-term technical vision. " Lead and mentor AI/ML engineers, data scientists, and cross-functional teams. " Evaluate emerging technologies and guide adoption of GenAI, LLMs, MLOps frameworks, and AI platforms. AI/ML Architecture & Innovation " Architect scalable, high-performance machine learning and GenAI solutions for NLP, CV, predictive analytics, and automation. " Design and optimize LLM-powered systems, including RAG pipelines, fine-tuned models, and enterprise AI assistants. " Develop reusable AI frameworks, components, and internal toolkits to accelerate organization-wide AI development. End-to-End AI System Development " Oversee full lifecycle: data architecture, feature engineering, experimentation, training, validation, deployment, and monitoring. " Build large-scale, cloud-native AI systems using Azure/AWS/GCP. " Establish standards for model quality, reliability, interpretability, and governance. MLOps & Platform Engineering " Architect robust MLOps pipelines CI/CD, model versioning, drift detection, automated retraining, monitoring. " Lead the development of AI platforms supporting multiple business teams and workloads. " Ensure production environments meet performance, scalability, and security requirements. Cross Functional Collaboration " Partner with executives, product teams, and business leaders to identify AI opportunities. " Translate complex business problems into scalable AI solutions. " Represent AI architecture in technical reviews and decision-making processes. " Databricks, SQL, and data processing frameworks.